Question

我有 2 个数据集并应用了 5 个不同的机器学习模型。

数据集 1：

def dataset_1():
    ...
    ...
    bike_data_hours = bike_data_hours[:500]
    X = bike_data_hours.iloc[:, :-1].values
    y = bike_data_hours.iloc[:, -1].values
    X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2)
    return X_train, X_test, y_train.reshape(-1, 1), y_test.reshape(-1, 1)

形状是(400, 14) (100, 14) (400, 1) (100, 1)。 dtypes: object (int64, float64).

数据集 2：

def dataset_2():
    ...
    ...
    final_movie_df = final_movie_df[:500]
    X = final_movie_df.iloc[:, :-1]
    y = final_movie_df.iloc[:, -1]
    gs = GroupShuffleSplit(n_splits=2, test_size=0.2)
    train_ix, test_ix = next(gs.split(X, y, groups=X.UserID))
    X_train = X.iloc[train_ix]
    y_train = y.iloc[train_ix]
    X_test = X.iloc[test_ix]
    y_test = y.iloc[test_ix]
    return X_train.shape, X_test.shape, y_train.values.reshape(-1,1).shape, y_test.values.reshape(-1,1).shape

形状是(400, 25) (100, 25) (400, 1) (100, 1)。 dtypes: object (int64, float64).

我正在使用不同的模型。代码是

    X_train, X_test, y_train, y_test = dataset
    fold_residuals, fold_dfs = [], []
    kf = KFold(n_splits=k, shuffle=True)
    for train_index, _ in kf.split(X_train):
        if reg_name == "RF" or reg_name == "SVR":
            preds = regressor.fit(X_train[train_index], y_train[train_index].ravel()).predict(X_test)
        elif reg_name == "Knn-5":
            preds = regressor.fit(X_train[train_index], np.ravel(y_train[train_index], order="C")).predict(X_test)
        else:
            preds = regressor.fit(X_train[train_index], y_train[train_index]).predict(X_test)

但我收到了一个常见错误，例如 this、this 和 this。我已经浏览了所有这些帖子，但对错误一无所知。我使用了 iloc 和 values 作为访问链接的解决方案。

preds = regressor.fit(X_train[train_index], y_train[train_index]).predict(X_test)
  File "/home/fgd/.local/lib/python3.8/site-packages/pandas/core/frame.py", line 3030, in __getitem__
    indexer = self.loc._get_listlike_indexer(key, axis=1, raise_missing=True)[1]
  File "/home/fgd/.local/lib/python3.8/site-packages/pandas/core/indexing.py", line 1266, in _get_listlike_indexer
    self._validate_read_indexer(keyarr, indexer, axis, raise_missing=raise_missing)
  File "/home/fgd/.local/lib/python3.8/site-packages/pandas/core/indexing.py", line 1308, in _validate_read_indexer
    raise KeyError(f"None of [{key}] are in the [{axis_name}]")
KeyError: "None of [Int64Index([  0,   1,   3,   4,   5,   6,   7,   9,  10,  11,\n            ...\n            387, 388, 389, 390, 391, 392, 393, 395, 397, 399],\n           dtype='int64', length=320)] are in the [columns]"

在这里，如果我使用 train_test_split 而不是 GroupShuffleSplit 则代码正在运行。但是，我想使用基于 GroupShuffleSplit 的 UserID，这样同一用户就不会同时进行训练和测试。您能告诉我在使用 GroupShuffleSplit 期间如何解决问题吗？

你能告诉我为什么我收到 dataset_2 的错误而 dataset_1 完全正常工作（并且 shape 和 dtypes）对于两个数据集是相同的.

Answer 1

您必须为 dataset_2 使用 values。做改变

    X_train = X.iloc[train_ix].values
    y_train = y.iloc[train_ix].values
    X_test = X.iloc[test_ix].values
    y_test = y.iloc[test_ix].values
    return X_train.shape, X_test.shape, y_train.reshape(-1,1).shape, y_test.reshape(-1,1).shape

希望现在能用

为什么我收到 GroupShuffleSplit（训练测试拆分）的错误

1 个答案: